Authors:
Piercarlo Dondi
and
Luca Lombardi
Affiliation:
University of Pavia, Italy
Keyword(s):
Time-of-Flight camera, Segmentation, Tracking, Mixed reality.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Human-Computer Interaction
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Segment Cluster Tracking
Abstract:
Time-of-Flight cameras are a new kind of sensors that use near-infrared light to provide distance measures of an environment. In this paper we present a very fast method for real-time segmentation and tracking, that exploits the peculiar characteristics of these devices. The foreground segmentation is achieved by a dynamic thresholding and region growing: an appropriate correction based on flexible intensity thresholding and mathematical morphology is used to partially compensate one of the most common problem of the TOF cameras, the noise generated by sun light. By the use of a Kalman filter for tracking the retrieved objects the system is able to correctly handle the occlusions and to follow multiple objects placed at different distances. The proposed system is our basic step for complex multimedia applications, such as augmented reality. An example of mixed reality that includes the integration of color information, supplied by a webcam is shown in the experimental results.